Florian Hartmann
b83546d833
Architecture (Agent 1):
- hermes_memory/tier2/{schema,facts,entities,relations,timeline}.py
- hermes_memory/tier3/{backend,chroma_backend,embedder}.py
- hermes_memory/graph/nx_store.py
- hermes_memory/api/memory_api.py (unified API)
- hermes_memory/cron/{consolidate,embed_queue,graph_refresh,prune}.py
- hermes_memory/config.py + pyproject.toml
Integration Plan (Agent 3):
- INTEGRATION_PLAN.md: Memory Provider Plugin strategy
- Hermes Core needs minimal changes
- sync_turn() + prefetch() hooks
- Skills integration via nextlevel_search/remember
Auto-Extraction (Agent 2):
- ARCHITECTURE.md: Full extraction pipeline docs
- Chunking, Pre-Filter, LLM Prompts, Classification
- Entity-Linking, Temporal Reasoning, Deduplication
All files: Python syntax checked, ECC standards applied.
36 lines
891 B
Python
36 lines
891 B
Python
"""Abstrakte Backend-Schnittstelle für Vektor-DBs."""
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from abc import ABC, abstractmethod
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from dataclasses import dataclass
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from typing import Dict, List
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@dataclass
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class SearchResult:
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chunk_id: str
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score: float
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text: str
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metadata: Dict
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class VectorBackend(ABC):
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@abstractmethod
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def index(self, chunks: List[str], payloads: List[Dict]) -> List[str]:
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"""Indexiert Chunks, gibt chunk_ids zurück."""
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...
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@abstractmethod
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def search(self, query_embedding: List[float], limit: int = 10, filters: Dict = None) -> List[SearchResult]:
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"""Semantische Suche mit Query-Embedding."""
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...
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@abstractmethod
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def delete(self, chunk_ids: List[str]) -> bool:
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"""Löscht Chunks anhand ihrer IDs."""
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...
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@abstractmethod
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def health(self) -> Dict:
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"""Gibt Status-Informationen zurück."""
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...
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